{"id":"W2168346060","doi":"10.1139/f08-156","title":"Evaluating the knowledge base for expanding low-trophic-level fisheries in Atlantic Canada","year":2008,"lang":"en","type":"article","venue":"Canadian Journal of Fisheries and Aquatic Sciences","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bedford Institute of Oceanography; Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada; Alfred P. Sloan Foundation","keywords":"Overexploitation; Fishery; Fisheries management; Stock assessment; Population; Fisheries science; Geography; Trophic level; Fish stock; Business; Fishing; Ecology; Biology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0215029,0.0003381915,0.0006648366,0.01882549,0.002139134,0.004155147,0.002250217,0.0007685357,0.002663788],"category_scores_gemma":[0.1144858,0.000256408,0.0007108207,0.01257335,0.001368727,0.002813667,0.001845013,0.0007737133,0.0002695711],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02086163,"about_ca_system_score_gemma":0.07793853,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8069501,"about_ca_topic_score_gemma":0.8817974,"domain_scores_codex":[0.9918404,0.001153013,0.001128334,0.0003810279,0.005060488,0.0004367769],"domain_scores_gemma":[0.7682937,0.096397,0.01931416,0.003957646,0.1056854,0.006352126],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003307731,0.0002589577,0.6253261,0.005162582,0.0005633991,0.0008789724,0.006537178,0.005733694,0.001265811,0.001921746,0.009605387,0.3424154],"study_design_scores_gemma":[0.00007135775,0.000218432,0.9200862,0.007838283,0.001196254,0.0003481427,0.0104624,0.006078603,0.002097374,0.002079439,0.04939961,0.0001238978],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8716991,0.0257114,0.003647186,0.01147029,0.0001395101,0.0007953438,0.02959383,0.000141174,0.05680211],"genre_scores_gemma":[0.9642179,0.01436942,0.00737481,0.0006720321,0.00006279337,0.0002109812,0.0116673,0.00001149427,0.001413213],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1930499,"threshold_uncertainty_score":0.3883736,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09581926664417555,"score_gpt":0.3040582212288765,"score_spread":0.208238954584701,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}